Differentiating among stages of cognitive impairment in aging: Version 3 of the Uniform Data Set (UDS) neuropsychological test battery and MoCA index scores
Bibliographic record
Abstract
INTRODUCTION: Federally funded Alzheimer's Disease Centers in the United States have been using a standardized neuropsychological test battery as part of the National Alzheimer's Coordinating Center Uniform Data Set (UDS) since 2005. Version 3 (V3) of the UDS replaced the previous version (V2) in 2015. We compared V2 and V3 neuropsychological tests with respect to their ability to distinguish among the Clinical Dementia Rating (CDR) global scores of 0, 0.5, and 1. METHODS: First, we matched participants receiving V2 tests (V2 cohort) and V3 tests (V3 cohort) in their cognitive functions using tests common to both versions. Then, we compared receiver-operating characteristic (ROC) area under the curve in differentiating CDRs for the remaining tests. RESULTS: Some V3 tests performed better than V2 tests in differentiating between CDR 0.5 and 0, but the improvement was limited to Caucasian participants. DISCUSSION: Further efforts to improve the ability for early identification of cognitive decline among diverse racial groups are required.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 0.007 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".